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Graph-structured data appears frequently in domains including chemistry, natural language semantics, social networks, and knowledge bases.
#2 best model for SQL-to-Text on WikiSQL
Our method first generates the node and graph embeddings using an improved graph-based neural network with a novel aggregation strategy to incorporate edge direction information in the node embeddings.
SOTA for SQL-to-Text on WikiSQL
Previous work approaches the SQL-to-text generation task using vanilla Seq2Seq models, which may not fully capture the inherent graph-structured information in SQL query.